| plotCSedges.tri {pcds.ugraph} | R Documentation |
The plot of the edges of the underlying or reflexivity graphs of the Central Similarity Proximity Catch Digraph (CS-PCD) for 2D data - one triangle case
Description
Plots the edges of the underlying or reflexivity graphs of
the Central Similarity Proximity Catch Digraph
(CS-PCD) whose vertices are the data points, Xp
and the triangle tri.
CS proximity regions
are constructed with respect to the triangle tri
with expansion parameter t > 0,
i.e., edges may exist only for Xp points inside the triangle tri.
Edge regions are based on center M=(m_1,m_2)
in Cartesian coordinates
or M=(\alpha,\beta,\gamma) in barycentric coordinates
in the interior of the triangle tri;
default is M=(1,1,1), i.e.,
the center of mass of tri.
With any interior center M,
the edge regions are constructed using the extensions
of the lines combining vertices with M.
See also (Ceyhan (2005, 2016)).
Usage
plotCSedges.tri(
Xp,
tri,
t,
M = c(1, 1, 1),
ugraph = c("underlying", "reflexivity"),
asp = NA,
main = NULL,
xlab = NULL,
ylab = NULL,
xlim = NULL,
ylim = NULL,
edge.reg = FALSE,
...
)
Arguments
Xp |
A set of 2D points which constitute the vertices of the underlying or reflexivity graphs of the CS-PCD. |
tri |
A |
t |
A positive real number which serves as the expansion parameter in CS proximity region. |
M |
A 2D point in Cartesian coordinates
or a 3D point in barycentric coordinates
which serves as a center in the interior of the triangle |
ugraph |
The type of the graph based on CS-PCDs,
|
asp |
A |
main |
An overall title for the plot (default= |
xlab, ylab |
Titles for the |
xlim, ylim |
Two |
edge.reg |
A logical argument to add edge regions to the plot,
default is |
... |
Additional |
Value
A plot of the edges of the underlying
or reflexivity graphs of the CS-PCD
whose vertices are the points in data set Xp
and the triangle tri
Author(s)
Elvan Ceyhan
References
Ceyhan E (2005).
An Investigation of Proximity Catch Digraphs in Delaunay Tessellations, also available as technical monograph titled Proximity Catch Digraphs: Auxiliary Tools, Properties, and Applications.
Ph.D. thesis, The Johns Hopkins University, Baltimore, MD, 21218.
Ceyhan E (2016).
“Edge Density of New Graph Types Based on a Random Digraph Family.”
Statistical Methodology, 33, 31-54.
See Also
plotCSedges, plotASedges.tri,
plotPEedges.tri, and plotCSarcs.tri
Examples
#\donttest{
A<-c(1,1); B<-c(2,0); C<-c(1.5,2);
Tr<-rbind(A,B,C);
n<-10
set.seed(1)
Xp<-pcds::runif.tri(n,Tr)$g
M<-as.numeric(pcds::runif.tri(1,Tr)$g)
t<-1.5
plotCSedges.tri(Xp,Tr,t,M,edge.reg = TRUE,xlab="",ylab="")
plotCSedges.tri(Xp,Tr,t,M,ugraph="r",edge.reg = TRUE,xlab="",ylab="")
#can add vertex labels and text to the figure (with edge regions)
Ds<-pcds::prj.cent2edges(Tr,M); cent.name="M"
txt<-rbind(Tr,M,Ds)
xc<-txt[,1]+c(-.02,.02,.02,.02,.04,-0.03,-.01)
yc<-txt[,2]+c(.02,.02,.02,.07,.02,.04,-.06)
txt.str<-c("A","B","C",cent.name,"D1","D2","D3")
text(xc,yc,txt.str)
#}